Skip to main content

Microbial community modeling based on cobrapy.

Project description

https://github.com/micom-dev/micom/raw/master/docs/source/_static/micom.png

actions status coverage pypi status

MICOM is a Python package for metabolic modeling of microbial communities currently developed in the Gibbons Lab at the Institute for Systems Biology and the Human Systems Biology Group of Prof. Osbaldo Resendis Antonio at the National Institute of Genomic Medicine Mexico.

MICOM allows you to construct a community model from a list on input COBRA models and manages exchange fluxes between individuals and individuals with the environment. It explicitly accounts for different abundances of individuals in the community and can thus incorporate data from 16S rRNA sequencing experiments. It allows optimization with a variety of algorithms modeling the trade-off between egoistic growth rate maximization and cooperative objectives.

Attribution

MICOM is published in

MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota
Christian Diener, Sean M. Gibbons, Osbaldo Resendis-Antonio
mSystems 5:e00606-19
https://doi.org/10.1128/mSystems.00606-19

Please cite this publication when referencing MICOM. Thanks :smile:

Installation

MICOM is available on PyPi and can be installed via

pip install micom

Getting started

Documentation can be found at https://micom-dev.github.io/micom .

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

micom-0.17.4.tar.gz (153.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

micom-0.17.4-py2.py3-none-any.whl (170.3 kB view details)

Uploaded Python 2Python 3

File details

Details for the file micom-0.17.4.tar.gz.

File metadata

  • Download URL: micom-0.17.4.tar.gz
  • Upload date:
  • Size: 153.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.8

File hashes

Hashes for micom-0.17.4.tar.gz
Algorithm Hash digest
SHA256 d6798cb68eaad41e3809ce6d36fbd6b9ce9086b3851d7dfb2d0100e6e588448d
MD5 c337ba9c65f42aed7d976b7d6e87a317
BLAKE2b-256 8706030736381a3c1e58d61101e9d2906fa004ae24131b1207bc4b38866f25b8

See more details on using hashes here.

File details

Details for the file micom-0.17.4-py2.py3-none-any.whl.

File metadata

  • Download URL: micom-0.17.4-py2.py3-none-any.whl
  • Upload date:
  • Size: 170.3 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/47.1.0 requests-toolbelt/0.9.1 tqdm/4.48.2 CPython/3.7.8

File hashes

Hashes for micom-0.17.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 baa85e52027511bc03ee0e87f6ef9243818f71b8bef14acfb0c420f2aec97f20
MD5 55aff646fec03e5e92c516e42d55bccf
BLAKE2b-256 a193233ea7264b62ccce563fa953e6f2d11dab2b4706a4bf5323c6ec8941d219

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page